Sienna Jackson

I deal with situations where companies will say, oh, we're making so much of a great impact in this and that way, or this, that, and the third. And I'm like the auditor who comes in and says, okay, all right, by what degree, by what measure are you making that impact? And who are your stakeholders? Who are you impacting and why and how? When it comes to generative AI currently, it uses up

I deal with situations where companies will say, oh, we're making so much of a great impact in this and that way, or this, that, and the third. And I'm like the auditor who comes in and says, okay, all right, by what degree, by what measure are you making that impact? And who are your stakeholders? Who are you impacting and why and how? When it comes to generative AI currently, it uses up

10 times more electricity. It's 10 to 30 times more energy. The demand for data centers has major environmental impacts. The mental health damage. There was a headline I saw recently about tenions who are being paid like pennies on the hour to train chatbots and algorithms. And they're just being fire hosed with the most energy. awful, disturbing content.

10 times more electricity. It's 10 to 30 times more energy. The demand for data centers has major environmental impacts. The mental health damage. There was a headline I saw recently about tenions who are being paid like pennies on the hour to train chatbots and algorithms. And they're just being fire hosed with the most energy. awful, disturbing content.

And they're having to like, so they're a real human. So it's not just a smart machine. There are human beings at the other end of the pipeline. A lot of them are actually really suffering to develop, to deliver this convenience to us, wealthy consumers. And I'm saying that as someone who, yeah, Gen AI is very convenient. It's very useful. Like I've used those tools. I've played with those tools.

And they're having to like, so they're a real human. So it's not just a smart machine. There are human beings at the other end of the pipeline. A lot of them are actually really suffering to develop, to deliver this convenience to us, wealthy consumers. And I'm saying that as someone who, yeah, Gen AI is very convenient. It's very useful. Like I've used those tools. I've played with those tools.

I think it's important for people to know and understand how those tools work. I think it's, it's important for us to like understand to not be afraid of learning about new technologies that are available because if we don't know them and understand them, other people will. And those are the people that are capitalizing on.

I think it's important for people to know and understand how those tools work. I think it's, it's important for us to like understand to not be afraid of learning about new technologies that are available because if we don't know them and understand them, other people will. And those are the people that are capitalizing on.

And if you think about like algorithmic bias now, think about the impact of using AI tools to evaluate health insurance claims. Think about the potential fallouts of using AI to evaluate a housing insurance claim. Because there are, I'm also a member of the National African American Insurance Association, so I have some feelers in the insurance industry.

And if you think about like algorithmic bias now, think about the impact of using AI tools to evaluate health insurance claims. Think about the potential fallouts of using AI to evaluate a housing insurance claim. Because there are, I'm also a member of the National African American Insurance Association, so I have some feelers in the insurance industry.

There's been some significant issues with bias, algorithmic bias on the axes of race when it comes to how these tools are applied to who gets it. an insurance policy or not, or how much coverage they receive or not. And you start to see patterns. So what a lot of Gen A does, it's garbage in, garbage out. It will just, it will reify or reinforce patterns. So if you're giving it biases...

There's been some significant issues with bias, algorithmic bias on the axes of race when it comes to how these tools are applied to who gets it. an insurance policy or not, or how much coverage they receive or not. And you start to see patterns. So what a lot of Gen A does, it's garbage in, garbage out. It will just, it will reify or reinforce patterns. So if you're giving it biases...

implicit or not, it's just going to reinforce those biases. The risks are pretty great when it comes to both the human costs and also the environmental costs, which is ultimately something that we foot the bill for as human beings. And then I think another thing to consider is just the spread of disinformation and deepfakes.

implicit or not, it's just going to reinforce those biases. The risks are pretty great when it comes to both the human costs and also the environmental costs, which is ultimately something that we foot the bill for as human beings. And then I think another thing to consider is just the spread of disinformation and deepfakes.

Now that Sora is available to the general public to pay subscribers, you're going to see a lot more flooding of our social media with altered images, right? Altered video that will look so convincing and so persuasive.

Now that Sora is available to the general public to pay subscribers, you're going to see a lot more flooding of our social media with altered images, right? Altered video that will look so convincing and so persuasive.

And if people don't develop the skill sets to recognize what is real and what is fake and how to differentiate, but the problem is like human brains are not good at differentiating between real and fake evidence. We tend to take things in as given and doing the critical thinking later of, wait, did that make sense? What I just saw? People don't really do that unless you really train them to do it.

And if people don't develop the skill sets to recognize what is real and what is fake and how to differentiate, but the problem is like human brains are not good at differentiating between real and fake evidence. We tend to take things in as given and doing the critical thinking later of, wait, did that make sense? What I just saw? People don't really do that unless you really train them to do it.

It's not our first instinct to be like, your first instinct is doom scroll and your brain is just vacuuming up what it sees and not saying, Hey, wait a second. That was how many fingers were on that hand? That's where we'll stop for now.

It's not our first instinct to be like, your first instinct is doom scroll and your brain is just vacuuming up what it sees and not saying, Hey, wait a second. That was how many fingers were on that hand? That's where we'll stop for now.